#!/usr/bin/python
# import the populate and dosurvey modules
import populate
import dosurvey
# run the Populate.generate script, setting parameters as necessary.
# the resulting model is stored in the variable 'pop'
# Any unspecified variables use the default values (see populate
# for more details)
pop = populate.generate(
1038,
surveyList=['PMSURV'],
radialDistType='lfl06',
siDistPars=[-1.41, 0.96], # non-standard SI distribution
duty=6.,
electronModel='lmt85',
nostdout=True # switches off output to stdout
)
# now run "dosurvey.run" on the model. Provide a list of surveys to use
surveyPopulations = dosurvey.run(pop, ['PMSURV'], nostdout=True)
# write out the survey results however you like
dosurvey.write(surveyPopulations, nores=False, summary=False, asc=False)
# write out the population model, if required
pop.write(outf="populate.model")
detections = np.full((runs_of_pop, runs_per_pop), 0)
#model_name = './1913_z330.model'
model_name = './1913_z330_varlum.model'
for xx, npop in enumerate(pops):
print "On population:{}".format(npop)
for ii in range(runs_of_pop):
pop = populate.generate(npop,
pDistPars=[log_p_1913, 0.0],
duty_percent=16.9,
orbits=False,
nostdout=True,
zscale=0.33,
siDistPars=[-1.4, 1.0],
lumDistPars=lum_params)
pop.write(outf=model_name)
for jj in range(runs_per_pop):
population = dosurvey.loadModel(model_name)
output = dosurvey.run(population, surveys, nostdout=True)
detections[ii][
jj] = output[0][2].ndet + output[1][2].ndet + output[2][
2].ndet + output[3][2].ndet + output[4][2].ndet
runs_per_pop = 100
detections = np.full((runs_of_pop, runs_per_pop), 0)
model_name = './0737B_z330.model'
for xx, npop in enumerate(pops):
print "On population:{}".format(npop)
for ii in range(runs_of_pop):
pop = populate.generate(npop,
pDistPars=[log_p_0737B, 0.0],
duty_percent=1.3,
orbits=False,
nostdout=True,
zscale=0.33,
siDistPars=[-1.4, 1.0])
pop.write(outf=model_name)
for jj in range(runs_per_pop):
population = dosurvey.loadModel(model_name)
output = dosurvey.run(population, surveys, nostdout=True)
detections[ii][
jj] = output[0][2].ndet + output[1][2].ndet + output[2][
2].ndet + output[3][2].ndet + output[4][2].ndet
#!/usr/bin/python
# import the populate and dosurvey modules
import populate
import dosurvey
# run the Populate.generate script, setting parameters as necessary.
# the resulting model is stored in the variable 'pop'
# Any unspecified variables use the default values (see populate
# for more details)
pop = populate.generate(1038,
surveyList=['PMSURV'],
radialDistType='lfl06',
siDistPars=[-1.41, 0.96], # non-standard SI distribution
duty=6.,
electronModel='lmt85',
nostdout=True # switches off output to stdout
)
# now run "dosurvey.run" on the model. Provide a list of surveys to use
surveyPopulations = dosurvey.run(pop, ['PMSURV'], nostdout=True)
# write out the survey results however you like
dosurvey.write(surveyPopulations, nores=False, summary=False, asc=False)
# write out the population model, if required
pop.write(outf="populate.model")
for jj, zzscale in enumerate(zscale):
print "On run:", jj
mean_z_hts = np.full(n_runs, 0.0)
mean_z_hts_err = np.full(n_runs, 0.0)
mean_dm_singb = np.full(n_runs, 0.0)
mean_dm_singb_err = np.full(n_runs, 0.0)
for ii in range(n_runs):
#Make sure to change the zscale!
pop = populate.generate(npop,
pDistType='unif',
surveyList=surveys,
pDistPars=[15, 70],
orbits=False,
nostdout=True,
zscale=zzscale,
siDistPars=[-1.4, 1.0])
#I set the allsurveyfile = True to combine detected PSR properties into single numpy array
op = dosurvey.run(pop, surveys, nostdout=True, allsurveyfile=True)
#Here I make use of the allsurveyfile, i.e. op[3]
mean_z_hts[ii] = np.nanmedian(
np.abs(op[-1][1].make_plotting_dicts()[1]['Gal Z']))
mean_z_hts_err[ii] = np.std(
np.abs(
op[-1][1].make_plotting_dicts()[1]['Gal Z'])) / np.sqrt(npop)
mean_dm_singb[ii] = np.nanmedian(
op[-1][1].make_plotting_dicts()[1]['DM'] * np.abs(
